class ImageTests(unittest.TestCase):
"""
Basically just tests that the Image API works and that Images act as Numpy arrays. There's very little going on
here other than simply storing data.
"""
def setUp(self):
array = np.array([[0, 1, 254], [45, 12, 9], [12, 12, 99]])
self.image = Image(array)
self.image.add_params(1200.314, 17, 2, 'GFP', 1)
def test_size(self):
self.assertEqual(self.image.height, 3)
self.assertEqual(self.image.width, 3)
def test_timestamp(self):
self.assertEqual(self.image.timestamp, 1.200314)
def test_frame_number(self):
self.assertEqual(self.image.frame_number, 17)
def test_fov(self):
self.assertEqual(self.image.field_of_view, 2)
def test_channel(self):
self.assertEqual(self.image.channel, 'GFP')
def test_z_level(self):
self.assertEqual(self.image.z_level, 1)
def test_slice(self):
subimage = self.image[:2, :2]
expected = np.array([[0, 1], [45, 12]])
self.assertTrue(np.array_equal(subimage, expected))
def get_image_by_attributes(self, frame_number, field_of_view, channel_name, z_level, height, width):
"""
Attempts to get Image based on attributes alone.
:type frame_number: int
:type field_of_view: int
:type channel_name: str
:type z_level: int
:type height: int
:type width: int
:rtype: Image or None
"""
image_group_number = self._calculate_image_group_number(frame_number, field_of_view, z_level)
try:
timestamp, raw_image_data = self._get_raw_image_data(image_group_number,
self._channel_offset[channel_name],
height,
width)
image = Image(raw_image_data)
image.add_params(image_group_number, timestamp, frame_number, field_of_view, channel_name, z_level)
except (TypeError, NoImageError):
return None
else:
return image
def get_image_by_attributes(self, frame_number, field_of_view,
channel_name, z_level, height, width):
"""
Attempts to get Image based on attributes alone.
:type frame_number: int
:type field_of_view: int
:type channel_name: str
:type z_level: int
:type height: int
:type width: int
:rtype: Image or None
"""
image_group_number = self._calculate_image_group_number(
frame_number, field_of_view, z_level)
try:
timestamp, raw_image_data = self._get_raw_image_data(
image_group_number, self._channel_offset[channel_name], height,
width)
image = Image(raw_image_data)
image.add_params(image_group_number, timestamp, frame_number,
field_of_view, channel_name, z_level)
except (TypeError, NoImageError):
return None
else:
return image
class ImageTests(unittest.TestCase):
"""
Basically just tests that the Image API works and that Images act as Numpy arrays. There's very little going on
here other than simply storing data.
"""
def setUp(self):
array = np.array([[0, 1, 254],
[45, 12, 9],
[12, 12, 99]])
self.image = Image(array)
self.image.add_params(1200.314, 17, 2, 'GFP', 1)
def test_size(self):
self.assertEqual(self.image.height, 3)
self.assertEqual(self.image.width, 3)
def test_timestamp(self):
self.assertEqual(self.image.timestamp, 1.200314)
def test_frame_number(self):
self.assertEqual(self.image.frame_number, 17)
def test_fov(self):
self.assertEqual(self.image.field_of_view, 2)
def test_channel(self):
self.assertEqual(self.image.channel, 'GFP')
def test_z_level(self):
self.assertEqual(self.image.z_level, 1)
def test_slice(self):
subimage = self.image[:2, :2]
expected = np.array([[0, 1],
[45, 12]])
self.assertTrue(np.array_equal(subimage, expected))
